Methods, apparatus and storage media for determining tissue marker locations

Abstract

This invention discloses a method, apparatus, and storage medium for determining tissue marking locations. The method includes acquiring the edge contour and hardness distribution information of a target tissue, wherein the hardness distribution information characterizes the hardness at different locations within the target tissue; determining a first candidate location to be marked in the target tissue region based on the shape characteristics of the edge contour; and determining locations where the hardness exceeds a hardness threshold as a second candidate location to be marked in the target tissue region based on the hardness distribution information; and determining the target location to be marked in the target tissue region based on the first and second candidate locations. This method allows for tissue marking without manual intervention, significantly improving the accuracy and efficiency of tissue marking.

Description

Technical Field

[0001] This invention relates to the field of biomedicine, and more specifically to a method, apparatus, and storage medium for determining the location of tissue markers. Background Technology

[0002] In existing technologies, treatment methods for tumor tissue, benign lesion tissue, and other tissues may include excision and drug therapy. When using drug therapy, the treated tissue can be marked with a marker to facilitate observation of the treatment progress. For example, the size and location of lesions on the tissue can be marked with the marker, allowing for assessment of treatment effectiveness based on the defined area during the treatment process.

[0003] Currently, the location of markers for tissues cannot be determined automatically and must be determined manually by medical staff, which results in low efficiency and low accuracy. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide a method, apparatus, device, and computer storage medium for determining tissue marker locations, which can improve marking efficiency and accuracy.

[0005] This invention provides a method for determining the location of tissue markers, the method comprising:

[0006] Obtain the edge contour and hardness distribution information of the target tissue, wherein the hardness distribution information is used to characterize the hardness at different locations of the target tissue;

[0007] Based on the shape characteristics of the edge contour, a first candidate location to be marked in the area where the target tissue is located is determined; and based on the hardness distribution information, locations where the hardness exceeds a hardness threshold are determined as second candidate locations to be marked in the area where the target tissue is located.

[0008] Based on the first alternative location and the second alternative location, the target location to be marked in the area where the target organization is located is determined.

[0009] In some embodiments, determining the target location to be marked within the region where the target organization is located, based on the first candidate location and the second candidate location, includes:

[0010] For any one of the first and second candidate locations, if the distance between the candidate location and all other candidate locations is greater than a distance threshold, then the candidate location is determined as the target location.

[0011] In some embodiments, determining the target location to be marked within the region where the target organization is located, based on the first candidate location and the second candidate location, includes:

[0012] For any one of the first candidate position and the second candidate position, if there is a target candidate position whose distance from the first candidate position and the second candidate position is not greater than a distance threshold, then the target position is determined based on the first candidate position and the target candidate position.

[0013] In some embodiments, determining the target location based on the alternative locations and the target alternative location includes:

[0014] If there is a target candidate location, then the location of the midpoint of the line connecting the candidate location and the target candidate location is determined as the target location;

[0015] If there are two or more target candidate locations, the midpoint of the area defined by the candidate location and the target candidate location shall be determined as the target location.

[0016] In some embodiments, determining the target location based on the alternative locations and the target alternative location includes:

[0017] The candidate location is determined as the target location, either the candidate location or the target candidate location.

[0018] In some embodiments, determining the first candidate location to be marked in the region where the target tissue is located based on the shape features of the edge contour includes:

[0019] In the case where there is a protrusion in the edge contour, the top and bottom positions of at least a portion of the protrusion are determined as the first alternative positions; and / or

[0020] In the case where the edge contour is recessed, the bottom position of at least part of the recess is determined as the first alternative position.

[0021] In some embodiments, determining the first candidate location to be marked in the region where the target tissue is located based on the shape features of the edge contour further includes:

[0022] If there are no protrusions on the edge contour, the area of ​​the region where the target tissue is located is detected. If the area of ​​the region where the target tissue is located is less than the area threshold, the center position of the region where the target tissue is located is taken as the first candidate position.

[0023] In some embodiments, obtaining the hardness distribution information of the target tissue includes:

[0024] Acquire quasi-static elastography data and / or shear wave elastography data of the target tissue, and obtain elastic distribution information of the target tissue based on the quasi-static elastography data and / or shear wave elastography data;

[0025] Acquire ultrasound imaging data of the target tissue, and based on the ultrasound imaging data, obtain the compositional distribution information and density distribution information of the target tissue;

[0026] The elasticity distribution information, the composition distribution information, and the density distribution information are fused and calculated to obtain the softness and hardness distribution information of the target tissue.

[0027] In another aspect, the present invention provides a device for determining the location of tissue markers, the device comprising:

[0028] The data acquisition module is used to acquire the edge contour and softness / hardness distribution information of the target tissue, wherein the softness / hardness distribution information is used to characterize the softness / hardness at different locations of the target tissue;

[0029] The alternative location determination module is used to determine a first alternative location to be marked in the region where the target tissue is located based on the shape features of the edge contour, and to determine locations where the softness or hardness exceeds a softness or hardness threshold as a second alternative location to be marked in the region where the target tissue is located based on the softness or hardness distribution information; and

[0030] The marker location determination module is used to determine the target location to be marked in the area where the target organization is located based on the first candidate location and the second candidate location.

[0031] In another aspect, the present invention provides a computer-readable storage medium for storing a computer program that, when executed by a processor, implements the method described above.

[0032] In another aspect, the present invention provides an electronic device comprising a processor and a memory, the memory being used to store a computer program which, when executed by the processor, implements the method described above.

[0033] In summary, in some embodiments of this application, by extracting the edge contour of the target tissue, a first candidate location to be marked in the area where the target tissue is located can be determined based on the shape features of the edge contour. By extracting the softness / hardness distribution information of the target tissue, locations in the target tissue where the softness / hardness exceeds a threshold can be obtained, thereby determining a second candidate location to be marked in the area where the target tissue is located. By fusing the first and second candidate locations, the target location to be marked in the area where the target tissue is located can be obtained. Thus, in the process of marking the target tissue, the target tissue can be marked without manual intervention, greatly improving the accuracy and efficiency of marking the target tissue. Attached Figure Description

[0034] The features and advantages of the invention will be more clearly understood by referring to the accompanying drawings, which are schematic and should not be construed as limiting the invention in any way. In the drawings:

[0035] Figure 1 A flowchart illustrating a method for determining tissue marker locations according to an embodiment of this application is shown;

[0036] Figure 2 This illustration shows a flowchart of obtaining hardness distribution information according to an embodiment of this application;

[0037] Figure 3 A schematic diagram of the edge contour of a target tissue provided in one embodiment of this application is shown;

[0038] Figure 4 A schematic diagram of the edge contour of a target tissue provided in another embodiment of this application is shown;

[0039] Figure 5 A schematic diagram of the functional modules of a tissue marker location determination device provided in one embodiment of this application is shown;

[0040] Figure 6 A schematic diagram of the structure of an electronic device provided in one embodiment of this application is shown. Detailed Implementation

[0041] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0042] This application proposes a method for determining the location of tissue markers in target tissue. This method automatically determines the marker location during the marking process, eliminating the need for medical personnel to manually determine the marker location, thereby improving the accuracy and efficiency of marker location determination. The target tissue is the tissue to be marked, which includes, but is not limited to, tumor tissue, benign lesion tissue, and nodules. The method for determining the tissue marker location can be applied to electronic devices. These electronic devices can be medical devices.

[0043] Alternatively, a marker clip can be used to mark the location.

[0044] In some embodiments, the length and width of the marker clip can be limited to within 5 mm, or the length and width of the marker clip can be set as needed.

[0045] In some embodiments, the surface of the marker clip may be smoothed or coated. The coating material may be a highly reflective ultrasonic material. A smoothed or coated marker clip can reflect more ultrasonic waves than the target tissue. Thus, based on the echo signals of the ultrasonic waves, the marker clip and the target tissue can be distinguished, thereby determining the location of the marker clip. Furthermore, to further improve the distinction between the marker clip and the target tissue, the marker clip can also be configured with a specific shape (e.g., S-shape). During ultrasonic testing, the location where the specified shape is detected is the location of the marker clip.

[0046] In some embodiments, the interior of the marking clip may contain a biocompatible material, and / or the exterior of the marking clip may be wrapped with a biocompatible material to facilitate compatibility between the marking clip and the target tissue. Additionally, the biocompatible material may contain hemostatic material, so that the marking clip, which marks the cut position after the target tissue has been rotary-cut, can function as a hemostatic agent.

[0047] In some embodiments, the tagging clips may be aseptically packaged to avoid infection of the target tissue at the tagging location.

[0048] Please see Figure 1 This is a flowchart illustrating a method for determining the location of tissue markers according to an embodiment of this application. Figure 1 In this study, the method for determining the location of tissue markers includes the following steps:

[0049] Step S11: Obtain the edge contour and hardness distribution information of the target tissue, wherein the hardness distribution information represents the hardness at different locations of the target tissue.

[0050] In some embodiments, the edge contour of the target tissue can be obtained from ultrasound imaging data of the target tissue. Those skilled in the art can obtain ultrasound imaging data using various techniques, which will not be elaborated upon here.

[0051] Please see Figure 2 This is a schematic diagram of the process for obtaining hardness distribution information according to an embodiment of this application. Figure 2 When obtaining information on the hardness distribution of a target tissue, the following steps may be included:

[0052] Step S21: Obtain quasi-static elastography data and / or shear wave elastography data of the target tissue, and obtain elastic distribution information of the target tissue based on the quasi-static elastography data and / or shear wave elastography data.

[0053] Specifically, quasi-static elastography data can be obtained by performing quasi-static elastography on the target tissue; shear wave elastography data can be obtained by performing shear wave elastography on the target tissue. Based on the quasi-static elastography data, the relative elastic information of the target tissue at different locations can be obtained, and based on the shear wave elastography data, the absolute elastic information of the target tissue at different locations can be obtained. The absolute elastic information can be shear wave velocity, elastic modulus, elastic modulus distribution characteristics, or other elastic parameters obtained from the quasi-static elastography data; there are no specific limitations. The relative elastic information can be strain, strain rate, strain ratio, or other elastic parameters obtained from the quasi-static elastography data; again, there are no specific limitations.

[0054] The relative elasticity information of the target organization at different locations refers to the elasticity characteristics of the target organization at each location compared to the elasticity at a specified location. For example, the elasticity at location A of the target organization is better or worse than the elasticity at location B. The absolute elasticity information of the target organization at different locations refers to the elastic modulus at each location of the target organization.

[0055] Based on shear wave elastography data, the elastic distribution information is determined by obtaining the elastic distribution information from the absolute elastic information of the target tissue at different locations.

[0056] The method for determining elasticity distribution information based on quasi-static elastography data is as follows: elasticity distribution information can be obtained based on the relative elasticity information of the target tissue at different locations.

[0057] Based on shear wave elastography data and quasi-static elastography data, the elasticity distribution information is determined as follows: for any location in the target tissue, the relative and absolute elasticity information at that location are fused to obtain the elasticity information at that location. The elasticity information at different locations in the target tissue can constitute the elasticity distribution information.

[0058] Step S22: Acquire ultrasound imaging data of the target tissue, and based on the ultrasound imaging data, obtain the compositional distribution information and density distribution information of the target tissue. Specifically, density distribution information can be obtained based on color Doppler ultrasound imaging data; compositional distribution information can be obtained based on B-mode ultrasound imaging data.

[0059] It should be noted that the acquisition of elasticity distribution information, composition distribution information, and density distribution information can be done in any order.

[0060] Step S23: The elasticity distribution information, composition distribution information and density distribution information are fused and calculated to obtain the softness and hardness distribution information of the target tissue.

[0061] Since elasticity, composition, and density can all reflect the softness or hardness of a tissue, the softness or hardness distribution of a target tissue can be determined based on the elasticity distribution, composition distribution, and density distribution information.

[0062] In this embodiment, elasticity distribution information, composition distribution information, and density distribution information can be input into a trained fusion model. The fusion model then performs fusion calculations on the elasticity distribution information, composition distribution information, and density distribution information to obtain the softness and hardness distribution information of the target tissue.

[0063] The trained fusion model can include the weights of elasticity distribution information, composition distribution information, and density distribution information. The fusion model performs calculations on the elasticity distribution information, composition distribution information, and density distribution information according to their respective weights to obtain the softness / hardness distribution information of the target tissue.

[0064] In some embodiments of this application, elastic imaging data and ultrasound imaging data are used to obtain the softness and hardness distribution information of the target tissue. The elasticity, composition and density of the target tissue are taken into account, so the softness and hardness distribution information obtained is more accurate, and thus the location to be marked can be determined more accurately.

[0065] Step S12: Based on the shape characteristics of the edge contour, determine the first candidate location to be marked in the area where the target tissue is located, and based on the softness and hardness distribution information, determine the location where the softness and hardness exceeds the threshold as the second candidate location to be marked in the area where the target tissue is located.

[0066] In some embodiments, a first alternative location determined based on the shape characteristics of the edge contour can be primarily used to define the area where the target tissue is located.

[0067] Specifically, when the edge contour has a convex shape, the top position of at least the partially convex shape can be determined as the first candidate position. When the edge contour has a concave shape, the bottom position of at least the partially concave shape can be determined as the first candidate position. For easier understanding, please refer to [link to relevant documentation]. Figure 3 This is a schematic diagram of the edge contour of a target organization provided in one embodiment of this application. Figure 3 In the diagram, on the edge contour of the target tissue, positions A, B, C, D, E, and F represent the top of the protrusions, while positions M1, M2, M3, and M4 represent the bottom of the indentation. These positions can all be considered as first-line candidate locations. After marking these positions, the area containing the target tissue can be determined based on the marked locations.

[0068] Furthermore, among the protrusions on the edge contour, target protrusions with heights exceeding a height threshold can be filtered out. If the location of the target protrusion can already define the area where the target tissue is located, then the location of the target protrusion can be used as the first candidate location, and the locations of other protrusions can be ignored. The height of the protrusion can refer to the distance between the bottom and the highest point of the protrusion. For easier understanding, please refer to [link to documentation]. Figure 4 This is a schematic diagram of the edge contour of a target tissue provided for another embodiment of this application. Figure 4 In the example, take protrusions D1 and E1. The height of protrusion D1 is h1, and the height of protrusion E1 is h2. Suppose that among protrusions A1 to E1, the heights of protrusions B1, D1, and E1 exceed the height threshold, while the heights of protrusions A1 and C1 do not exceed the height threshold. In this case, the positions of protrusions B1, D1, and E1 can be used as the first candidate positions, and the positions of protrusions A1 and C1 can be ignored.

[0069] In some embodiments, when there are no protrusions in the edge contour, the area of ​​the target tissue region can be detected. If the area of ​​the target tissue region is less than an area threshold, the center position of the target tissue region is used as the first candidate position. It is understood that when there are no protrusions in the edge contour, the edge contour of the target tissue can be a regular geometric shape, such as a circle. In this case, if the area of ​​the target tissue is small (less than the area threshold), the center position of the target tissue region can be directly used as the marker position. Furthermore, when observing the target tissue, extending a certain distance outward from the marker position can determine the area where the target tissue is located. This reduces the number of marker positions for the target tissue.

[0070] If the edge contour of the target tissue has no protrusions and its area is not less than the area threshold, a first alternative position can be specified at preset intervals on the edge contour. In this way, the area where the target tissue is located can be determined by the marked positions at preset intervals on the edge contour.

[0071] In some embodiments, the second alternative locations determined based on the hardness distribution information of the target tissue are primarily used to define areas within the target tissue that require focused attention. Simply put, locations within the target tissue where the hardness exceeds a threshold are typically areas of significant hardening. These locations can be marked for focused monitoring.

[0072] In summary, based on the distribution information of the softness and hardness of the target tissue and the shape characteristics of its edge contour, the first and second candidate locations that need to be marked in the target tissue can be determined.

[0073] Step S13: Determine the target location to be marked in the area where the target tissue is located based on the first alternative location and the second alternative location.

[0074] In some embodiments, for any one of the first and second candidate locations, if the distance between the candidate location and all other candidate locations is greater than a distance threshold, then the candidate location is determined as the target location. For example... Figure 4 In this case, assuming that the distance between the first candidate position B1 and other candidate positions is greater than the distance threshold, then the first candidate position B1 can be determined as the target position.

[0075] In some embodiments, for any one of the first alternative location and the second alternative location, if there is a target alternative location whose distance from the first alternative location and the second alternative location is not greater than a distance threshold, then the target location is determined based on the alternative location and the target alternative location.

[0076] Specifically, if there is a candidate location, the location of the midpoint of the line connecting the candidate location and the target candidate location is determined as the target location. For example... Figure 4 In this case, assuming that the distance between the first candidate position D1 and the second candidate position F1 is less than the distance threshold, the position of the midpoint of the line connecting these two candidate positions can be used as the target position.

[0077] If there are two or more candidate locations, the midpoint of the area defined by the candidate location and the target candidate location is determined as the target location. For example... Figure 4In this case, assuming that the distance between the first candidate position A1 and the second candidate position F2, and the distance between the first candidate position A1 and the second candidate position F3 are both less than the distance threshold, then the first candidate position A1, the second candidate position F2, and F3 can be connected in pairs, and the area defined by the connecting lines can be used as the area defined by the candidate position and the target candidate position, and the midpoint of the area (i.e., F2) can be used as the target position.

[0078] In some embodiments, either the alternative location or the target alternative location can be determined as the target location. For example... Figure 4 In this context, for the first alternative position D1 and the second alternative position F1, either the first alternative position D1 or the second alternative position F1 can be used as the target position. For example... Figure 4 In the above, for the first alternative position A1, the second alternative position F2, and F3, the first alternative position A1 can be used as the target position, or the second alternative position F2 can be used as the target position, or the second alternative position F3 can be used as the target position.

[0079] In summary, in some embodiments of this application, by extracting the edge contour of the target tissue, a first candidate location to be marked in the region of the target tissue can be determined based on the shape features of the edge contour. By extracting the softness / hardness distribution information of the target tissue, locations in the target tissue where the softness / hardness exceeds a threshold can be obtained, thereby determining a second candidate location to be marked in the region of the target tissue. By fusing the first and second candidate locations, the target location to be marked in the region of the target tissue can be obtained. Thus, in the process of marking the target tissue, manual marking of the target tissue is eliminated, greatly improving the accuracy and efficiency of marking the target tissue.

[0080] Please see Figure 5 This is a functional module diagram of a tissue marker location determination device provided in one embodiment of this application. The tissue marker location determination device includes:

[0081] The data acquisition module is used to acquire the edge contour and hardness distribution information of the target tissue, wherein the hardness distribution information is used to characterize the hardness at different locations of the target tissue;

[0082] The alternative location determination module is used to determine a first alternative location to be marked in the region where the target tissue is located based on the shape features of the edge contour, and to determine locations where the softness or hardness exceeds a softness or hardness threshold as a second alternative location to be marked in the region where the target tissue is located based on the softness or hardness distribution information; and

[0083] The marking location determination module is used to determine the target location to be marked in the area where the target organization is located, based on the first candidate location and the determined second candidate location.

[0084] Please see Figure 6 This is a schematic diagram of the structure of an electronic device provided in one embodiment of this application. The electronic device includes a processor and a memory. The memory stores a computer program, which, when executed by the processor, implements the aforementioned method for determining the location of tissue markers.

[0085] The processor can be a central processing unit (CPU). It can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or combinations thereof.

[0086] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as the program instructions / modules corresponding to the methods in the embodiments of this invention. The processor executes various functional applications and data processing by running the non-transitory software programs, instructions, and modules stored in the memory, thereby implementing the methods described in the above embodiments.

[0087] One embodiment of this application also provides a computer-readable storage medium for storing a computer program that, when executed by a processor, implements the above-described method for determining the location of tissue markers.

[0088] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for determining the location of tissue markers, characterized in that, The method includes: Obtain the edge contour and hardness distribution information of the target tissue, wherein the hardness distribution information is used to characterize the hardness at different locations of the target tissue; Based on the shape characteristics of the edge contour, a first candidate location to be marked in the area where the target tissue is located is determined; and based on the hardness distribution information, locations where the hardness exceeds a hardness threshold are determined as second candidate locations to be marked in the area where the target tissue is located. Based on the first alternative location and the second alternative location, determine the target location to be marked in the area where the target organization is located; The acquisition of the softness / hardness distribution information of the target tissue includes: Acquire quasi-static elastography data and shear wave elastography data of the target tissue, and obtain elastic distribution information of the target tissue based on the quasi-static elastography data and shear wave elastography data; Acquire ultrasound imaging data of the target tissue, and based on the ultrasound imaging data, obtain the compositional distribution information and density distribution information of the target tissue; By using a trained fusion model, the elasticity distribution information, the composition distribution information, and the density distribution information are fused and calculated to obtain the softness and hardness distribution information of the target tissue.

2. The method as described in claim 1, characterized in that, The step of determining the target location to be marked in the area where the target organization is located based on the first candidate location and the second candidate location includes: For any one of the first and second candidate locations, if the distance between the candidate location and all other candidate locations is greater than a distance threshold, then the candidate location is determined as the target location.

3. The method as described in claim 1, characterized in that, The step of determining the target location to be marked in the area where the target organization is located based on the first candidate location and the second candidate location includes: For any one of the first candidate position and the second candidate position, if there is a target candidate position whose distance from the first candidate position and the second candidate position is not greater than a distance threshold, then the target position is determined based on the first candidate position and the target candidate position.

4. The method as described in claim 3, characterized in that, Determining the target location based on the candidate locations and the target candidate locations includes: If there is a target candidate location, then the location of the midpoint of the line connecting the candidate location and the target candidate location is determined as the target location; If there are two or more target candidate locations, the midpoint of the area defined by the candidate location and the target candidate location shall be determined as the target location.

5. The method as described in claim 3, characterized in that, Determining the target location based on the candidate locations and the target candidate locations includes: The candidate location is determined as the target location, either the candidate location or the target candidate location.

6. The method as described in claim 1, characterized in that, The step of determining the first candidate location to be marked in the region where the target tissue is located based on the shape features of the edge contour includes: In the case where there is a protrusion on the edge contour, the top position of at least part of the protrusion is determined as the first alternative position; and / or In the case where the edge contour is recessed, the bottom position of at least part of the recess is determined as the first alternative position.

7. The method as described in claim 6, characterized in that, The step of determining the first candidate location to be marked in the region where the target tissue is located based on the shape features of the edge contour further includes: If there are no protrusions on the edge contour, the area of ​​the region where the target tissue is located is detected. If the area of ​​the region where the target tissue is located is less than the area threshold, the center position of the region where the target tissue is located is taken as the first candidate position.

8. A device for determining the location of a tissue marker, characterized in that, The device includes: A data acquisition module is used to acquire the edge contour and hardness distribution information of a target tissue, wherein the hardness distribution information is used to characterize the hardness at different locations of the target tissue; wherein acquiring the edge contour and hardness distribution information of the target tissue includes: acquiring quasi-static elastography data and shear wave elastography data of the target tissue, and obtaining the elasticity distribution information of the target tissue based on the quasi-static elastography data and shear wave elastography data; acquiring ultrasound imaging data of the target tissue, and obtaining the composition distribution information and density distribution information of the target tissue based on the ultrasound imaging data; and fusing and calculating the elasticity distribution information, the composition distribution information, and the density distribution information using a trained fusion model to obtain the hardness distribution information of the target tissue. The alternative location determination module is used to determine a first alternative location to be marked in the region where the target tissue is located based on the shape features of the edge contour, and to determine locations where the softness or hardness exceeds a softness or hardness threshold as a second alternative location to be marked in the region where the target tissue is located based on the softness or hardness distribution information; and The marker location determination module is used to determine the target location to be marked in the area where the target organization is located based on the first candidate location and the second candidate location.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store a computer program that, when executed by a processor, implements the method as described in any one of claims 1 to 7.

10. An electronic device, characterized in that, The electronic device includes a processor and a memory, the memory being used to store a computer program that, when executed by the processor, implements the method as described in any one of claims 1 to 7.

Images